In a recent INMA blog post, we discussed the role of mass personalisation on the future of journalism. In this post, we will respond to a question received from that post: “What are the challenges preventing publishers from implementing a mass personalisation strategy?”

The short answer to this question is that bringing actionable customer insights into business processes is the obstacle preventing publishers from personalising their customer interactions.

Operationalising customer insights requires not only technology tools but process changes, personnel training, and alignment of the actions across functions and communication channels. Lastly, effective performance measurement and testing are needed to validate the success of personalisation in improving business outcomes.

It can be a difficult process to personalise offerings and communication, but there are some shortcuts.
It can be a difficult process to personalise offerings and communication, but there are some shortcuts.

Since the last post was published, an article was published by NiemanLab about a publisher that has developed a paywall targeted to individual readers. The paywall gives each reader a score that reflects their propensity to subscribe, which then determines how much content they are allowed to sample before receiving a subscription offer.

This publisher has built this system over two or three years. What should other publishers do that may not have the same resources or wish to implement a targeted paywall sooner?

Before we answer that question, I would mention this type of paywall was one of the opportunities for personalisation discussed in the last post. In full disclosure, we are working on this type of paywall with more than 40 news media sites, and we had seen a presentation by the publisher in the NiemanLab article at a recent INMA event.

Other opportunities for personalisation mentioned in the last post are event-triggered communications for engagement, retention, and acquisition and personalised product offerings — an area where research into content economics and consumption is leading to innovation in product design and resource allocation for newsrooms.

To return to the case study of the personalised paywall, let’s identify some of the requirements of that personalised solution:

  • The paywall will need to be able to serve different experiences, and possibly subscription offers, to individual readers.
  • The publisher must score the reader for propensity to subscribe and pass that information to the paywall.
  • The propensity scoring algorithm requires data on the reader in near-real time from his current and prior activity on the site.
  • Other factors relevant to the touchpoint decision must also be available when the personalised action is taken.

Most paywall solutions have the ability to differentiate the experience for readers based on customer attributes. A propensity score can be one of those attributes, and the score can be passed to the paywall application without issue in most cases. The calculation of the propensity score requires data on the reader from prior visits and from his current activity.

Capturing customer-level data (that is not sampled) and preparing that data for use in a scoring algorithm is a significant challenge for many publishers, particularly if that data comes from multiple sources. Other information, such as the advertising revenue potential for the individual or offline data about that reader, is needed to maximise total digital revenue.

This paywall example describes the key challenge of mass personalisation: bringing actionable customer insights to a touchpoint often requires significant data processing and scoring calculations on a large scale in a timely and accurate manner. Site speed is an important feature of the user experience, and the personalisation activity will lose much of its effectiveness if it negatively affects a reader’s experience on the site.

In many cases, the investment in resources and time required to personalise the paywall is not worth the incremental audience revenue for a publisher if it builds the solution internally. We are helping publishers achieve this outcome quickly at a reasonable cost, and there are software tools that can help.

One last comment on the paywall case: Besides the analytical and technological aspects of this project, marketing and customer communication also play key roles. Knowing how best to frame an offer to a customer segment is vital to the success of personalised touchpoints.

Not all touchpoints require such significant resources and complexity to effectively personalise interactions with a customer. We recommend starting with touchpoints that have significant financial roles to the organisation and are currently one-size-fits-all, supported by systems that can accommodate targeted actions, and measurable.

Inbound customer service is one example. One news media company we work with realised its customer service group brought in more revenue than its digital advertising function, yet it paid relatively little attention and had made minimal investments in analytics for this group.

Providing customer service representatives (CSRs) with the relative value of individual customers and a suggested retention offer (or upsell offer) for them is a straightforward and inexpensive process. Measuring the call outcomes of individual CSRs identifies the effectiveness of those suggested offers and the performance of CSRs relative to their peers.

Starting with a proof-of-concept (POC) project to personalise one touchpoint is an effective way to begin. A project with a modest scope and well-defined outcomes will limit the risk of delays and provide helpful insights into the resources and system interfaces required. The POC will identify the people, processes, and technologies involved in the touchpoint to be personalised. As the organisation gains experience with personalisation, and sees the ROI on those efforts, more complex touchpoints can be tackled.

Extending personalisation across a customer’s relationship with your company will yield significant returns. For publishers where data privacy regulations may affect personalised actions, there are compromises that can be made until more clarity on the subject is available.

Please follow up with questions on this topic if you have them. We are happy to share case studies and provide introductions to leading companies in the industry. Often, those questions provide good topics for future blog posts, which are always welcome.